An improved A* and path smoothing algorithm was proposed to overcome the defects of A* based paths for unmanned boats in inland lake environments including collision avoidance insufficiency, maneuver redundancy, and steering non-smoothness. Firstly, the evaluation function was enhanced by incorporating obstacle avoidance and steering costs. Secondly, the redundant path of the A* algorithm was removed by iteratively generating the segmentations in a reversal manner. Finally, the steering trajectory was further optimized by addressing steering performance of the unmanned boat. Simulation experiments on a real inland lake map show that the improved algorithm significantly reduces the collision probability, steering angle and traveling distance, simultaneously, and thereby improving the steering performance of the unmanned boat.

Due to inherent scattering and absorption, underwater images inevitably suffer from multiple degradations arising from blurring, low contrast and color distortion, thereby seriously deteriorating visual perception. In this paper, a deep learning-based underwater image restoration and enhancement framework (UIRENet) was proposed by virtue of depth estimation and gradient descent strategy. With the aid of convolutional and nonlinear activation function modules, a deep perception network was constructed to achieve scene depth perception maps for different degradation regions, thereby overcoming the dependence of scene depth degradation. A gradient optimization strategy was further proposed to optimize the parameters of convolutional networks and improve the performance of deep network enhancement. Combined with perceptual, edge and underwater color constancy losses, a comprehensive loss function for underwater image enhancement networks was rationally formed.  Comprehensive experiments on the UIEB-90, UIEB-M and EUVP datasets show that the UIRENet framework significantly outperforms  typical underwater image enhancement methods in terms of reducing underwater image blurriness and improving visual effects. In particular, comparing to CLAHE, ICM, GC, IBLA, DCP, ULAP, FUnIE-GAN, UGAN and Uformer, the objective evaluation metric UIQM can be promoted by 0.3700, 0.6446, 0.5919, 1.3081,1.3032, 1.1672, 0.0593, 0.1329 and 0.0934, respectively.

In order to solve the problems of complex navigation scenes of inland waterway vessels, few shape and color characteristics of marine radar images, and the difficulty of annotation, an improved YOLOv8 marine radar image target detection method was proposed. Firstly,  to alleviate the issues of annotation errors and model overfitting, a label smoothing strategy was introduced during the model training phase. Then, combining the unique positional prior information of the radar images, a coordinate-based convolution structure was designed to simultaneously extract the shape, color and positional features of the target. To verify the effectiveness and superiority of the proposed method, comparative experiments were conducted on the collected radar images of the Yangtze River channel  under different weather conditions. Results show that the proposed method achieves an accuracy rate of 91.52% while ensuring real-time object detection, with an average accuracy  improvement of  5.17% compared to the classic YOLOv8, which can provide technical support for improving the modernization and intelligent management level of inland waterway shipping.

In order to improve the control performance of the fault-tolerant permanent magnet vernier rim-driven motor (FTPMV-RDM) position sensorless control system, the speed controller and rotor position estimation algorithm of the system were studied. A fast super-twisting sliding mode controller was used to reduce the chattering phenomenon existing in traditional sliding mode controller, and an adaptive sliding mode observer was used to estimate the rotor position to improve the position estimation accuracy. A simulation model of the FTPMV-RDM position sensorless control system was built in the Matlab/Simulink environment. The simulation results show that the control method proposed in this paper can accurately estimate the speed and rotor position information of FTPMV-RDM in the absence of fault and one-phase open-circuit fault, and the system has good dynamic and static performance.

Considering the asymmetry of market size between shipping companies in the shipping service supply chain, by using Stackelberg game theory, a three-stage sequential game model between shipping companies and freight forwarders was established to determine the optimal encroachment and pricing strategies of shipping companies, and the impact of market share on shipping company encroaching decisions and supply chain member pricing decisions was studied. Results show that whether shipping companies encroach or not, the higher market share always brings more profits to shipping companies; when the market share of the shipping company is high, the substitution degree of transportation services between shipping companies is low, and the encroachment cost is high, the shipping company will gain more profits without encroachment; when the shippers have a higher or lower preference for encroaching channel, the encroachment will bring more benefits to the shipping company.

Aiming at an innovative engineering structure spanning the bay, the submerged floating tunnel (SFT), the three-dimensional solid model of SFT was established by using ABAQUS finite element analysis software, and taking the SFT design scheme of Funkawan Bay in Japan as the object. The lateral deformation and torsional motion response characteristics of the SFT were analyzed under the conditions of single cable break and multiple cables continuous break, and the influence of Weight-Buoyancy Ratio (WBR) on cable break response was discussed through parameter sensitivity analysis. The results show that the maximum torsional angle response and vertical displacement response of two consecutive anchor cable failures at the mid span increase by nearly three times and double respectively compared to a single anchor cable failure. Increasing the safety factor of the cable is significantly important to avoid continuous cable-breaking. In addition, the SFT equivalent model for dynamic responses analysis is proposed, which can accurately reflect the dynamic characteristics of the whole tunnel and the deformation characteristics under various loads.

In order to effectively utilize the large amount of boil off gas (BOG) generated during the operation of liquefied natural gas (LNG) ships, the ship allocation problem for LNG sea transportation routes considering BOG management was studied. A ship allocation model was established for LNG sea transportation routes at economical speeds using BOG generated from LNG as propulsion fuel. On this basis, a BOG management strategy was designed based on the relationship between ship speed and BOG demand, while a joint optimization model for LNG sea transportation route allocation and ship speed considering BOG management was established. Taking an LNG shipping company in China as an example, the lowest cost, optimal ship allocation plan, and voyage schedule corresponding to two models were obtained. Comparing the optimal solutions of the two models, it can be seen that the BOG management strategy can effectively reduce costs by more than 8%, while corresponding management suggestions are proposed from the perspective of LNG spot price fluctuations and the business scale of shipping companies. Research results show that the proposed method can provide decision support for LNG shipping companies to reasonably allocate transportation resources and effectively manage LNG ship evaporation gas.

A finite control set model predictive control strategy based on the improved virtual space vector (IVSV-FCSMPC) was proposed for DC side midpoint potential imbalance problem of midpoint-clamped three-level rectifiers. Firstly, based on multi-vector synthesis and the characteristic that virtual space vectors do not cause midpoint potential fluctuations,a single-objective value function based on current tracking control was constructed to achieve unweighted coefficient based predictive control. Secondly, a dynamic adjustment factor based on midpoint potential feedback was designed to adjust the action time of positive and negative small vectors and medium vectors in the vector synthesis process. Two pairs of redundant small vectors were simultaneously adjusted within the small sector range of the low modulation regime. In the small sector range of the high modulation regime without redundant vector action, the virtual space vector switch sequence was optimized by improving the virtual medium vector to suppress midpoint potential fluctuations, achieving precise control of midpoint potential balance within the full modulation regime range. Finally, the experimental verification was carried out based on the hardware platform of the three-level rectifier. Results show that the designed control method has good current tracking control performance, excellent midpoint potential balance control and fast response speed.

A self-following dual-mode obstacle avoidance model predictive control method based on improved dynamic window method was proposed for the trajectory tracking control problem of unmanned surface vehicle (USV) formation under the influence of sudden obstacles. Firstly, the longitudinal velocity and bow angular velocity oscillation constraints were introduced to reduce the jitter of the velocity and bow angle in the design of the evaluation function of the dynamic window algorithm so as to achieve better integration of obstacle avoidance planning and control. A strategy of calculating the steering azimuth based on intermediate distance was proposed to reduce the sharp turns in the obstacle avoidance process of the USV, while an evaluation term based on the deviation of the predicted and the expected position ending was designed. Meanwhile, the formation keeping information was combined to correct the obstacle avoidance endpoint and reduce the deviation of the USV formation. Secondly, based on the linearized Taylor expansion principle, a prediction model for USV formation was designed. The prediction value of the model was corrected by the prediction error between the system output measurement and the model prediction values. At the same time, a rolling finite time domain iterative online optimization strategy was adopted to propose a trajectory tracking model prediction control method for USV formation that integrated autonomous following dual-mode obstacle avoidance strategy. Finally, a nonlinear disturbance observer was designed to compensate the environmental disturbances, while the Lyapunov function was constructed to prove the stability of the system by combining with the terminal penalty theory. Eventually, the effectiveness and reliability of the proposed USV formation obstacle avoidance and trajectory tracking control algorithm were verified by simulation experiments.

To investigate the influence of different pressure relief port areas on the evolution of hydrogen-air flame morphology, a self-built experimental platform was used for hydrogen-air explosions experiments , and OpenFOAM open-source software was used for numerical simulation to analyze the detonation characteristics and flame morphology under different pressure relief port areas (0%, 25%, 50%, 75%, 100%). Results show that the area of the pressure relief port has little effect on the flame shape, but it affects the timing of flame formation. As the area of the pressure relief port increases, the propagation speed of the tulip-flame increases, the detonation pressure decreases, and the peak appearance time is delayed. The change in pressure relief port area affects the flow field structure of unburned gas and thus affects the flame shape. A smaller pressure relief port area is conducive to the formation of vortex structures in unburned gas, promoting the formation of flat plate flames and tulip flames. The area of the pressure relief port  is an important factor affecting the shape and detonation characteristics of hydrogen flames. By optimizing the structural parameters of the pressure relief port, the propagation speed  and detonation pressure of hydrogen flames can be effectively controlled, reducing the risk of explosion and having significant implications for the safe use of  hydrogen energy.

To optimize the trajectory planning problem of underactuated ship automatic berthing and avoid getting stuck in local optima, a real-time trajectory planning method considering the overall constraints of the ship kinematic model and obstacle constraints was proposed. Based on the gridded map, the A* algorithm was used to plan the global optimal path, and the redundant point deletion strategy was applied to obtain the reference waypoints for trajectory planning. Considering that ship berthing was a dynamic process, the extended dynamic window algorithm (EDWA) was used to predict the berthing trajectory of the ship during the constant force stage and deceleration stage, and the proportional integral derivative (PID) control method was introduced to adjust the ship’s heading. After conducting feasibility tests on all predicted trajectories, the optimal trajectory was obtained by using an evaluation function that considers constraints such as target points, reference waypoints, and obstacles, and the corresponding force was used as the control input for the ship. Repeat the above steps for realtime planning based on the current control input and motion state of the ship at the next sampling time until the ship reached the target point. The feasibility of the proposed method was verified by using the simulation scenario of Rizhao port. Results show that the proposed method can guide ships to avoid obstacles and reach the designated berth in a relatively short time, the distance between the trajectory and the nearest obstacle is 144.1428 m, and the trajectory length is 47.26 m longer than the traditional A*+EDWA, however, the planning time is reduced by 55.12%, which show the superiority of the proposed method.

A dual-branch residual convolutional neural network was proposed for image enhancement in PIV velocity technique to obtain high-quality particle images. Firstly, a dual-branch convolutional neural network composed of residual blocks was designed to extract features from the input particle image pairs, while a coding-decoder was used to effectively fuse the feature information of the particle image pairs. Secondly, a challenging image enhancement dataset was autonomously generated to train model parameters, including Gaussian noises of different concentrations, light intensity noise and various real interference backgrounds, thereby fully simulating real fluid scenes. Results show that the proposed method can effectively deal with noise interference in both synthesized and real images, achieving image enhancement. Meanwhile， higher precision velocity fields can be obtained by using velocity field estimation algorithm to process the particle image pairs enhanced by the proposed method in this paper.

With the rapid development of science and technology, multi-unmanned ship systems have shown great potential in military, rescue and escort mission scenarios. The purpose of this paper is to explore the formation construction problem of multiple unmanned surface vehicle systems based on multi-agent deep reinforcement learning algorithm. Considering the sluggish convergence speed of the conventional multi-agent deep deterministic policy gradient algorithm (MADDPG), this study incorporates the attention mechanism into the value function stage to enhance the convergence speed of the formation decision model for a multi-UAV system. Through the cooperation of the formation model of the unmanned surface vehicle with the formation collision avoidance and the formation construction reward function, the efficiency of the multi-UAV to complete the formation construction task is finally improved. The simulation results conclusively demonstrate the efficacy of the proposed method in accomplishing multi-unmanned surface vehicle formation construction tasks, thereby establishing a solid theoretical foundation for future applications of multi-unmanned ship formation construction.

Aiming at the problem of poor performance of traditional predictive function control (PFC) in speed control due to external disturbances, parameter mismatches, and measurement and control quantization errors caused by position sensors in the servo control system of permanent magnet synchronous motor (PMSM), an optimized predictive function control method was used by using a composite adaptive position observer. The composite adaptive observer was constructed by combining model reference adaptive control (MRAC)  with extended state observer (ESO) to improve the locationless observer observation accuracy and disturbance resistance, accurately detected rotor information, and used it as feedforward compensation for the predictive function controller, which achieved fast and high performance control of the overall servo system. The experimental results show that the improved  predictive function control has feasibility and superiority in response speed and disturbance suppression under sudden changes in load and speed.

In order to study the influence of panic emotion transmission among passenger ship personnel, a P-SEIRS panic emotion infection model was established based on the personality OCEAN model and SEIRS infectious disease model. A personnel evacuation model considering panic emotion infection was established by using Anylogic evacuation simulation software, the evacuation process of passenger ship personnel under panic emotion transmission was analyzed, and the influence of initial panic personnel proportion, sensitivity, equipment intervention, and number of guides on panic emotion transmission and evacuation efficiency was explored. The simulation results show that panicked individuals will exacerbate congestion, leading to an increase in evacuation time; the higher the sensitivity of the crowd, the faster the spread of panic emotions, and more panicked pedestrians will be generated during the evacuation process; equipment intervention and appropriate guidance are beneficial for improving passenger evacuation efficiency, but excessive guidance can prolong evacuation time.

In order to improve the speed and accuracy of water level prediction, a prediction model based on improved echo state network (ESN) was proposed. Xavier method was introduced to optimize the weights to adapt to the water level prediction task. At the same time, the concept drift detection method (EDDM) was introduced to adapt to the actual water level environment, monitor the change of water level data distribution, and trigger the corresponding model update or adaptation strategy when the concept drift was detected, so as to improve the prediction effect of the real water level. The experimental results of data from nine water level stations show that compared to traditional sequence prediction models (SVM, RNN, GRU, LSTM, ESN, and XESN(Xavier-ESN)), the proposed model shows higher prediction accuracy for each water level station in terms of overall prediction performance and short -term, medium - term and long-term predictions, further improving the prediction accuracy of  inland waterway water level.

In order to explore the influence of factors such as water content of foamed asphalt, cement/lime, asphalt aging degree and temperature on the interface characteristics of foamed asphalt cold recycling binder (composed of cement/lime, aging asphalt and foamed asphalt, hereinafter referred to as binder), molecular dynamics method was used to build different types of binder molecular models, and the interface energy, interaction energy, cohesive energy density (CED) and water molecule radial distribution function (RDF) were used as the calculation indicators to quantitatively analyze the interface characteristics of each component material in the binder, thus revealing the microscopic mechanism of interaction between each component material. Results show that, in terms of the same material properties of other components, the binder with long-term aging asphalt (LTAA) exhibits lower interfacial energy, interaction energy, CED and water molecules RDF compared to binder with short-term aging asphalt (STAA). When the moisture content of foamed asphalt in binder is 2.4%, the interfacial energy, interaction energy, CED and water molecular RDF of binder are the highest, and when the moisture content of foamed asphalt in binder is 1.8%, the interfacial energy, interaction energy, CED and water molecular RDF of binder are the lowest. Compared with lime characterized by CH, cement binder characterized by CSH has higher interfacial energy and interaction energy, but its CED and water molecule RDF are lower.  When the temperature is 303 K~308 K, the binder containing STAA has higher interface energy and interaction energy than the binder containing LTAA, but that is opposite when the temperature is 313 K~318 K, and the CED of the binder basically remains stabilization as the temperature increases. Compared with the cementing material containing CH, the cementing material containing CSH has higher interfacial energy and interaction energy, which gradually increases with the increase of temperature and reach the highest value at 318 K, however, the CED of the both remains stabilization. As the temperature increases, the RDF of water molecules in different binders also increases, and a large number of water molecules concentrate towards the ends, which has a negative impact on the interfacial characteristics of binders.

In order to improve loading efficiency, focusing on the pre-marshalling problem and taking the priority of the slot-storage export containers as the main decision variable, a priority model for the pre-marshalling problem of export containers in storage yard was proposed. Considering containers flipping operations as the core objective of the decision process, a transcoding technique was introduced based on the properties of decimal and binary conversion. Combining with existing research models and the proposed integer programming model, a set of transcoding models were constructed. By testing on existing data sets, compared with existing models, the proposed priority model can reduce the average solution time by 75.66%,while the solution time of the transcoding model group is significantly lower than that of the original model group, in addition that the maximum solution efficiency is increased by 182.5%.

Focusing on the core audience of the Mobility as a Service （MaaS）service platform, namely public transportation users, this study aimed to investigate the underlying mechanisms of their willingness to use the MaaS service platform and gained a deeper understanding of the driving factors that encouraged this group to use MaaS services. This paper divided the public transportation user group into passive passenger group and selective passenger group. Based on the questionnaire survey data of Dalian City, Liaoning Province, a multi-index and multi-factor structural equation model was used to deeply explore the satisfaction level of these two groups with the current level of public transportation services, and their attitudes and behavioral intentions toward using MaaS services. Research has found that passengers’ attitudes and willingness to use MaaS services are positively correlated with their satisfaction with public transportation services, but there are mechanism differences between the two types of passengers in the process of converting satisfaction into MaaS usage willingness. Selective passengers’ satisfaction directly converts into usage intention, while passive passengers first change their attitudes towards MaaS, thereby affecting their usage behavior. Therefore, when promoting MaaS services, differentiated strategies should be developed for different passenger groups，that is，for selective passengers, the efficiency and convenience of MaaS services should be highlighted, while for passive passengers, the quality of MaaS services and environmental comfort should be reflected. In addition, factors such as gender, age, and transfer frequency also affect the willingness to use MaaS. The above findings provide decision-making basis for relevant departments to plan MaaS service platforms, optimize public transportation services, and improve MaaS penetration rates.

In order to explore the influence of cavity leakage flow on the aerodynamic performance and flow field structure of the annular diffuser cascade, the annular diffuser cascade was studied based on the verified numerical simulation method, and the effects of leakage flow rate and circumferential velocity on corner separation and total pressure loss were analyzed. Results show that as the leakage flow increases, the expansion range of the passage vortex (PV) becomes larger, the corner separation occurs earlier, and the total pressure loss coefficient of the blade gradually increases.When the leakage flow coefficient increases to 1.5%, the total pressure loss coefficient expands by 22.9% . The increase in circumferential velocity of the leakage flow improves the blockage situation in the near end wall area.The degree of deflection of the fluid close to the end wall towards the suction surface is weakened, and the range of deflection  is reduced. When the circumferential velocity coefficient increases to 1.1, the total pressure loss  coefficient  decreases by 21.3%.

Vessel-borne stabilization platforms can isolate vessel-borne equipment from vessel motions and ensure the operation safety of vessel-borne equipment. For a three-degree-of-freedom parallel vessel-borne stabilization platform, a wave compensation control hardware-in-the-loop (HIL) simulator is developed by using a personal computer (PC) and OP4510 real-time computer, as well as MATLAB and AMESim software for testing the performance of vessel-borne stabilization platform wave compensation controllers, which can reduce the test cost and the risk of sea trial, and shorten the development cycle of vessel-borne stabilization platform wave compensation controllers. The developed HIL simulator is used to test the performance of a joint space wave compensation stabilization controller as an example. The test results indicate that the joint space wave compensation stabilization controller can guarantee that the supporting surface of the vessel-borne platform is maintained at a desired horizontal position and orientation, while verifying that the developed HIL simulator can be used to test the performance of vessel-borne stabilization platform wave compensation controllers.

When optimizing the reservation quota scheme, existing methods faced many challenges, including difficulty in capturing dynamics and randomness, limited theoretical assumptions, and complex data acquisition and processing. GPS trajectory data of container trucks was used to comprehensively capture the entire process of container truck turnover from arrival at the port to completion of operations, and based on this, establishes a mapping relationship between the number of container truck arrivals within the unit appointment time window and their total turnover time at the port. A more precise and concise quota optimization model was constructed by using this mapping relationship, and the quota appointment system for container trucks was optimized and solved. The experimental results show that the optimized reservation quota scheme effectively reduces the arrival volume of container trucks during peak periods, while increasing the number of vehicles arriving during off peak periods, significantly reducing the total turnover time of container trucks at the port, improving the operational efficiency of the terminal, and thereby enhancing the competitiveness of the port.

 In order to address the challenges encountered in intelligent ship global path planning using the DQN algorithm, such as paths being planned too close to obstacles, excessive turning points, large turning angles, and slow algorithm convergence, a method based on Noisy DQN (NoisyNet-DQN) for global path planning is proposed. Firstly, to maintain a safe distance between intelligent ships and obstacles, and to reduce path turning points and large turning angles, additional reward functions including heading reward, time reward, turning point reward, and safety reward are incorporated on top of the traditional reward function. Secondly, to tackle the slow convergence issue in complex navigation scenarios, parameter noise is introduced into the output layer of the DQN neural network, thereby enhancing the convergence speed of the DQN network. Simulation studies are conducted in the actual maritime environments of Dalian and Zhoushan. The simulation results indicate that compared to the traditional DQN algorithm, the proposed Noise-DQN algorithm significantly improves the convergence speed and, greatly enhances the safety and economy of the planned global path, better aligning with the actual navigation requirements of ships. The research results can provide a certain reference for global path planning in intelligent ship navigation.

To avoid the phenomenon of parameter drift caused by dynamic cancellation in identification modeling stage of unmanned surface vessel (USV), two measures of parallel processing and estimation of too large and too small initial values were combined to form a comprehensive application method, and on this basis, a nonlinear innovation identification algorithm was proposed. Experimental results show that the proposed algorithm avoids the drift phenomenon of hydrodynamic coefficients and improves the ability to reprocess historical data. The algorithms have the characteristics of strong solving ability, high identification efficiency, and low computational burden, laying the foundation for stable navigation of USV in interference environments.

In order to accurately predict the stiffness of the elastic squirrel cage structure, the genetic algorithm based on the stiffness theoretical formulation was adopted to optimize the geometric parameters of the squirrel cage, and a three-dimensional finite element model for the optimized squirrel cage was established. The stiffness of a squirrel cage under Remote force and Bearing load were calculated and compared by using ANSYS software, and the effect of root fillet dimensions on the stiffness of the squirrel cage was analyzed. An elastic cage stiffness experimental system was designed and built, and the stiffness test results of the elastic cage specimens were compared with the numerical simulation results. The results show that the deviation between the stiffness calculated by finite element method using Remote force and Bearing load and the stiffness tested in the experiment is within 3%. In the engineering design analysis of elastic cages, the finite element method can significantly improve the prediction accuracy of the stiffness of elastic cages compared to the theoretical formula method.

A low Reynolds number flow simulation around a cylinder for non-zero mean oscillatory inflow was carried out to study the differences in stress and flow field morphology of structures under different oscillation periods. Firstly, based on the self-developed underwater flow field simulation software zFlower, a module for inlet boundary conditions under unsteady inflow was developed. On the basis of a uniform and fully developed flow field, oscillation flow simulations with high and low frequency ratios were carried out to obtain the force state of the cylinder and the evolution process of the flow field under oscillation flow conditions. Results show that when the frequency of the incoming flow is high, the oscillating incoming flow will affect the vortex shedding morphology of the flow, while the peak transverse force on the cylinder is relatively large. Meanwhile, when the incoming frequency is low, the absolute value of the lateral force acting on the structure does not change significantly, but the frequency spectrum of the force is complex, which may make it easier to excite the flow induced vibration of the structure.

Bank slope siltation and pile foundation cracking damage are common issues in coastal port high-piled wharves in China, posing a significant threat to the safe operation of the wharves. To implement effective maintenance measures, such as bank slope desilting and pile repair, the primary task is to understand the cracking mechanism of wharf piles under bank slope siltation. The paper investigated the siltation status of bank slopes of 16 major coastal ports in Jiangsu and Zhejiang regions, as well as the cracking of pile foundations of 7 typical wharves. Based on specific engineering, finite element models of the interaction between silted bank slope and wharf pile foundations were established, and the force and deformation characteristics of the pile-soil system were analyzed. The plastic deformation state of the pile foundation, as determined by the internal force combination value, was largely consistent with the actual location of the wharf pile cracking axis. This confirmed the validity of the modeling approach. A total of seven factors were selected for orthogonal testing in terms of both the engineering geological conditions of the bank slope and the structural parameters of the piled wharf, and the sensitivity of each factor to the internal force of the pile foundation was determined using extreme deviation analysis. The main conclusions are as follows. In marine environment, sediment continues to silt back under and behind piled wharf can cause sustained deformation of soft soil layers, leading to the passive pile problem. As the bank slope is silted, the soil beneath the wharf moves significantly towards the sea, causing large horizontal displacement of neighboring piles. This leads to a surge in the axial force and bending moment of the pile foundations, which in turn induces the top or the maximum pile displacement of some piles to exceed the limit of elastic-plastic deformation. Moreover, during the siltation process, the shoreward sloping piles at the rear of the wharf have greater additional internal forces, making them more susceptible to cracking and damage. The axial force and bending moment at the top of the piles under siltation conditions are more sensitive to the structure parameters and the slope of the bank slope.

To improve the conversion rate of HC in natural gas/diesel dual fuel engines under low load, a three-way catalytic converter based on reverse flow was designed, and a mathematical model of the chemical reaction process of HC and CO catalytic conversion in a single channel was established, which was solved by ANSYS FLUENT software, while the numerical simulation of the working characteristics of the reverse flow three-way catalytic converter was carried out. Results show that the designed reverse flow three-way catalytic converter can effectively control the emission of HC when the engine is under low load condition. The flow direction transformation operation significantly improves the conversion rates of HC and CO compared to unidirectional flow. If the influence of shift mutation is ignored, the conversion rate of HC and CO is increased by 3.9%~6.4% and 2.0%~2.7%, respectively, while the conversion rate of NO_x is relatively low, i.e., only about 0.6%. The design of the switch time of the converter is not easy to be too large or too small, and it is recommended that the switch time is 10 s~15 s. With the increase of inlet velocity, the maximum temperature of the converter decreases, while the emissions of HC and CO increase and the conversion rate decreases, but the impact on the conversion of NO_x is small.

The issue of reclaiming scheduling in dry bulk terminal yards was examined, with the objective of enhancing operational efficiency, minimizing delays, and optimizing the advantages of ship loading mixing operations. An optimization model was developed to schedule the reclaiming operations at a dry bulk terminal, considering the loading mixing process, in order to reduce delays. The integrated optimization of reclaiming scheme formulation, stacking position allocation, and reclaimer scheduling was conducted, by considering constraints such as dynamic yard storage of various goods, mutual interference of reclaimer operations, and proportional synchronous reclaiming of multiple stacking positions. Based on the characteristics of the problem and model, a heuristic algorithm was designed to efficiently solve large-scale problems by using adaptive large neighborhood search. The experimental results show that, compared to a general solver, the method proposed in this paper can obtain high-quality material retrieval scheduling schemes for large-scale cases within 1 hour. Compared with the squeaking wheel algorithm, the average improvement of the objective function value in solving large-scale cases is 19.9%. Meanwhile, this method comprehensively considers the integrated optimization of stacking allocation and reclaimer scheduling for mixed loading. Compared with the results obtained without considering mixed loading, the total delay of reclaimer operations reduced by an average of 28.35%，which can provide theoretical support for dry bulk terminals to allocate yard resources and plan operations when considering mixed loading process.

To address the issue that navigational drag performance of an unmanned quadramaran is affected by both longitudinal and lateral separations of multi-bodies, the entire layout of an self-designed unmanned quadramaran is optimized by comprehensively comparing drag coefficients of various schemes under different navigation conditions. Firstly, a variety of layout schemes are constructed to compare and analyze calm-water resistance coefficients under three different speed conditions by using computational fluid dynamics numerical simulation methods and Fluent solver. Secondly, a comprehensive resistance coefficient evaluation function is designed to optimize the layout scheme considering resistance performance. Finally, the improvement effect of layout optimization on the overall navigation performance is further verified by comparing the wave height and surface pressure before and after optimization. Simulation results show that the longitudinal distance is the main factor affecting the overall navigation resistance of quadramaran, while the optimized layout of multi-bodies reduces the comprehensive resistance coefficient by 12.9% compared to that before optimization, thereby effectively reducing wave height and surface pressure of the unmanned quadramaran during navigation.

To realize the non-contact measurement of propeller geometric parameters, a region growing algorithm based on adaptive octree was proposed to extract the point cloud model of an propeller. Firstly, the adaptive octree was utilized to partition the point cloud data into non-uniform voxels. Secondly, by combining with the spatial connectivity and smoothness of voxels, the region growth criteria were set, such the feature attributes of voxels were utilized for region growth to extract the propeller point cloud model. Then, the orthogonal experimental method was used to optimize the algorithm parameters. Finally, a comparative experiment was conducted between the proposed algorithm and the traditional octree based region growing algorithm as well as the point based region growing algorithm. Results show that the algorithm can achieve accurate extraction of the propeller point cloud model, while the segmentation accuracy can reach 99.5%, which is 1.8% and 1.3% higher than the other two algorithms. The execution time is 1045 ms, which is 4.1% and 5.6% of the other two algorithms. The efficiency of point cloud segmentation can be significantly improved.

Multi-phase permanent magnet fault-tolerant motors are often used in aviation, transportation and military fields which require high reliability of drive systems. Open circuit fault is a common electrical fault in motor drive system. Aiming at the problems that the existing fault diagnosis methods need to identify the open circuit fault of switch tube and winding with multiple sets of variables, and the change of motor running state is easy to lead to the misdiagnosis of threshold value judgment, this paper proposes a new phase voltage average value algorithm, which combines the motor drive system with the current mode flux observer. and switches the diagnosis variables from fault complex identification to a group of variables identification, and from threshold range diagnosis to a group of positive and negative variables the different open circuit faults of switching tube and winding can be distinguished by the diagnostic results. The experimental platform for fault diagnosis of six-phase permanent magnet fault-tolerant motor is built, and the experimental results verify the effectiveness and superiority of the proposed algorithm.

The feature differentiation of different categories of ship targets in SAR images is not clear, and the recognition accuracy may decrease when there are many ship categories. To better extract category features, this paper proposed a recognition model DCN-MSF-TR, which drawed on the idea of Transformer encoder-decoder and added a deformable convolutional module (DCN) to the backbone network. At the same time, the feature layers processed by Transformer multi-scale self attention were fused at appropriate positions in the model in a feature pyramid manner, and each layer can not only utilize its own information, but also comprehensively utilize the features of other layers. The validation results on the Open SARShip-3-Complex three class dataset and Open SARShip-6-Complex six class dataset show that the average recognition accuracy reaches 78.1% and 66.7%, respectively, which show that the proposed method can more effectively identify ship categories in SAR images compared to other recognition models.

In order to explore the influence mechanism of cleaning agent on the cleaning effect of chemical tanker during tank washing, palm oil cleaning experiment was carried out based on self-built experimental platform. Combined with FLUENT numerical simulation, the influence of cleaning water temperature and ethanol concentration in cleaning water on the cleaning effect of palm oil was systematically analyzed. The results showed that with the increase of cleaning water temperature, the adhesion of residual palm oil was decreased, and the cleaning effect of residual palm oil on the wall was accelerated at the initial stage of washing (0-8s). The cleaning speed of cleaning water at 30℃ and 40℃ was 3%/s and 6%/s, respectively, which was significantly higher than that of cleaning water at 20℃. With the increase of the concentration of cleaning agent added to the rinsing water, the viscosity of the oil alcohol mixture is critically affected. In the early stage of rinsing (0-8s), the higher concentration of cleaning water can effectively reduce the viscosity of the palm oil-ethanol mixture, thus improving the cleaning effect. With the extension of washing time (8-15s), the influence of cleaning water concentration on cleaning effect is gradually weakened. The influence degree of cleaning water temperature and concentration on the cleaning effect is compared, and it is found that the cleaning water concentration has a great influence on the cleaning effect at 0-2s and 12-15s, and the cleaning water temperature plays a key role in the cleaning effect at 5-10s. In order to reduce the consumption of cleaning agent and shorten the cleaning time, it is recommended to use cleaning water mixed with high concentration of cleaning agent to quickly flush the chemical tank during the pre-washing stage. After pre-washing, rinse the chemical tank with hot water.

Aiming at the nonlinear and strong coupling characteristics of AUV 6-DOF motion, a Deep bidirectional Temporal Convolutional Networks based on dung beetle optimization (DBO) is proposed in this paper as a nonlinear system identification modeling method. First, a bidirectional Temporal Convolutional Networks (BiTCN), a bidirectional Gated Recurrent Unit (BiGRU), and an Attention mechanism (self-attention) are used to construct a Deep bidirectional Temporal Convolutional Networks (Deep-BiTCN) to establish a 6-DOF nonlinear black-box model of the AUV. Secondly, in order to improve the accuracy of Deep-TCN model prediction, this paper uses DBO algorithm to optimize the model hyper-parameters. Finally, the validity and feasibility of the motion modeling method in this paper are verified by comparing with support vector machine (SVM) and random forest (RF) model. The experimental results show that, compared with Deep-BiTCN, the root mean square error (RMSE) and symmetric mean absolute percentage error (SMAPE) of the DBO-Deep-BiTCN algorithm model are reduced by 58.94% and 49.22%, respectively, and the coefficient of determination (R2) is improved by 0.73%; the AUV 6-DOF motion model based on DBO-Deep-BiTCN has high accuracy and strong convergence, and avoids the motion nonlinearity leads to the problems of large forecast error and easy dispersion of the motion system under strong coupling, which can provide an effective strategy for AUV 6-DOF motion identification.

To investigate the influence of sediment soil parameters to pile foundations of piled wharf to force deformation, a numerical computational model of the interaction system of bank slope and piled wharf is established, Firstly, extensive fiducial error is used to identify the key siltation stages during bank slope siltation process. Furthermore, the Sobol’ and TGP global sensitivity analysis method are also employed to analyze the sensitivity of the sediment soil parameters to the force deformation of pile foundations. On this basis, a normalized sensitivity index (SVI) method is utilized to determinate the importance of cohesion, friction angle, Young’s modulus, and Poisson's ratio in influencing the force deformation of the pile foundations. The computational results show that the Young’s modulus is the primary driving factor for affecting the force deformation of pile foundations. And the sensitivity of the pile foundation to horizontal displacement at the mudline is not influenced by sediment thickness, with the importance ranking as follows: Young’s modulus, cohesion, Poisson's ratio, and friction angle. The quantitative findings of this study contribute to a deeper understanding of the influence of sediment soil parameters on the force deformation of pile foundations during bank slope siltation process, which can provide valuable theoretical references for the engineering design and reliability assessment of the interaction system of bank slope and piled wharf. 

Considering the impact of the boundary width of the emission control area (ECA), a mixed-integer nonlinear programming model is established with the objective of minimizing the total operational costs of the vessel, thereby optimizing emission reduction strategies and sailing speed. The Southeast Asian route of a certain company is taken as an example for solution and sensitivity analysis. Results show that the cost comparison of different emission reduction schemes is mainly affected by the level of fuel oil prices, while carbon taxes have no impact on the cost comparison results of different schemes. From the current various fuel oil prices, desulfurization towers installation is the most economical emission reduction measure, which is followed by the ECA internal and external fuel conversion strategy, using MGO fuel strategy, and using LNG fuel strategy, respectively. As the width of ECA decreases and the difference in fuel oil prices decreases, the cost of fuel conversion schemes will be lower than that of installing desulfurization towers. When the initial investment cost of using LNG fuel is reduced to 80% or less, or the price of LNG fuel is reduced to 50% or less, while the price of MGO fuel is invariable or higher, the cost of using LNG fuel will be lower than that of using MGO fuel. The setting of the ECA width will affect the emission reduction strategy of shipping companies, while by appropriately increasing the width of the ECA, the behavior of ship companies switching fuels inside and outside the ECA can be reduced.

In order to solve the limitation on communication and computation resources, and complex wireless environments in maritime three-dimensional communication-computing converged networks, the computation offloading scheme for Intelligent Reflecting Surface (IRS) mounted on Unmanned Aerial Vehicle (UIRS)-assisted maritime communication-computing converged networks was studied. The offloading ratios of Unmanned Surface Vehicles (USVs), computation resource allocation of edge server, UIRS phase shifts and deployment were jointly optimized, aiming at minimizing the total energy consumption. Due to the high-dimensional coupled variables, based on the iterative optimization method, the original problem is decomposed into two subproblems, where the relaxation method and Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm were used to solve the offloading ratios and communication-computing resources, respectively. Simulation results show that the proposed scheme can minimize the total energy consumption while satisfying the latency requirements, and perform superior performance under various scenarios. Moreover, in comparison with the scheme of without IRS, the total energy consumption in the proposed scheme is reduced by 42.0% on average.

A fixed-time sliding mode fault-tolerant control strategy based on a disturbance observer is proposed for the cooperative encirclement control of multiple unmanned surface vehicles (USVs) with actuator faults and unknown environmental disturbances. The method is grounded in the hierarchical control concept, where the cooperative encirclement system is decoupled into a guidance layer and a control layer. Firstly, in the guidance layer, a fixed-time distributed cooperative control law combined with a sideslip angle observer (SO) is designed to achieve equidistant rotation around the target. Secondly, in the control layer, actuator faults are treated as disturbances affecting the layer, and a fixed-time disturbance observer (FxDO) is introduced to observe the nonlinear lumped disturbances caused by actuator faults and unknown environmental factors in real-time. A fixed-time sliding mode controller (FxSMC) is then designed to compensate for these disturbances, ensuring fast convergence of dynamic errors while smoothing the control output. Finally, the stability of the closed-loop control system is proven using the Lyapunov function, and the effectiveness of the proposed method in mitigating the adverse effects of actuator faults on the cooperative encirclement task is validated through a comparative simulation involving three USVs.